Risk Factors and Predictive Nomogram for Survival in Elderly Patients with Brain Glioma.

OBJECTIVE: To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram. METHODS: Data from elderly individuals (age ≥65 years) histologically diagnosed with brain glioma were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio. Additionally, data obtained from Tangdu Hospital constituted an external validation cohort for the study. The identification of independent prognostic factors was achieved through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, enabling the construction of a nomogram. Model performance was evaluated using C-index, ROC curves, calibration plot and decision curve analysis (DCA). RESULTS: A cohort of 20 483 elderly glioma patients was selected from the SEER database. Five prognostic factors (age, marital status, histological type, stage, and treatment) were found to significantly impact overall survival (OS) and cancer-specific survival (CSS), with tumor location emerging as a sixth variable independently linked to CSS. Subsequently, nomogram models were developed to predict the probabilities of survival at 6, 12, and 24 months. The assessment findings from the validation queue indicate a that the model exhibited strong performance. CONCLUSION: Our nomograms serve as valuable prognostic tools for assessing the survival probability of elderly glioma patients. They can potentially assist in risk stratification and clinical decision-making.

Whole mitochondrial genome sequence for an osteoarthritis model of Guinea pig (Caviidae; Cavia).

Animal models played an important role in osteoarthritis studies. Here, the complete mitochondrial genome sequence of the Guinea pig was reported for the first time. The total length of the mitogenome was 16,797 bp. It contained the typical structure, including two ribosomal RNA genes, 13 protein-coding genes, 22 transfer RNA genes and one non-coding control region (D-loop region). The overall composition of the mitogenome was estimated to be 34.9% for A, 26.1% for T, 26.0% for C and 13.0% for G showing an A-T (61.0%)-rich feature. This mitochondrial genome sequence will provide new genetic resource into osteoarthritis disease.